High-throughput Methodology
High-throughput Methodology - Related Videos
09:44
High-throughput Screening for Chemical Modulators of Post-transcriptionally Regulated Genes
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2015
Here we describe a cell-based reporter gene assay as a valuable tool to screen chemical libraries for compounds modulating post-transcriptional control mechanisms exerted through 3’ UTR.
08:18
Methodology for Studying Interactions of Vitamin A Membrane Receptors and Opsin Protein with their Ligands in Generating the Retinylidene Protein
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Cited by 3 •
2024
Here, we describe two quantitative methods for studying the protein-ligand interactions of vitamin A membrane receptors and photoreceptor opsin with their respective physiological ligands.
06:19
High-Throughput Screening to Obtain Crystal Hits for Protein Crystallography
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Cited by 16 •
2023
This protocol details high-throughput crystallization screening, ranging from the 1,536 microassay plate preparation to the end of a 6 week experimental time window. Details are included about the sample setup, the imaging obtained, and how users can perform analyses using an artificial intelligence-enabled graphical user interface to quickly and efficiently identify macromolecular crystallization conditions.
01:35
Introduction to New Approach Methodologies (NAMs)
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2026
All animal procedures described here must be conducted in accordance with institutional animal ethics guidelines and approved by IACUC. All procedures must follow the principles of the 3Rs—Replacement, Reduction, and Refinement—and must be performed by trained personnel. New approach methodologies (NAMs) are innovative scientific approaches that generate biological data while reducing reliance on traditional vertebrate animal models. As part of the broader effort to implement the principles of...
07:07
Synthetic Methodology for Asymmetric Ferrocene Derived Bio-conjugate Systems via Solid Phase Resin-based Methodology
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Cited by 2 •
2015
The synthesis of asymmetric species of ferrocene is challenging using solution techniques. This report focuses on the methods carried out to produce a ferrocene-biotin bioconjugate using facile and clean reactions accomplished via solid-phase synthesis. Incorporation of a thiolate moiety is shown to impart the ability for immobilization on gold surfaces.
FAQs
Miniaturized assays, automation, and parallel processing work together by allowing many experimental conditions to be handled within a coordinated system. Standardized workflows then make measurements more comparable across samples, while computational analysis organizes the resulting dataset for interpretation. This combination supports systematic comparisons rather than isolated observations.
Standardized workflows are important because high-throughput studies generate measurements across many samples or conditions. Applying the same workflow improves consistency, making differences between experimental groups easier to evaluate. In immunology and infection research, this consistency helps distinguish recurring immune or pathogen-associated patterns from variation introduced by the way assays are performed.
Computational analysis helps convert extensive measurements into interpretable comparisons by examining results across samples and conditions rather than treating each assay as an isolated observation. Its value is especially apparent when repeated patterns emerge from immune-cell responses or pathogen-associated signals. These patterns can guide interpretation of host-pathogen experiments and support data-driven conclusions.
Compared with individual assays, high-throughput methodology examines many samples, measurements, or conditions in parallel. The broader sampling can expose patterns that a single assay might not show, while standardized workflows improve consistency across the comparison. This makes the approach useful for systematic biological investigation when multiple responses or conditions must be evaluated together.
A high-throughput study can link miniaturized assays with automation and parallel processing, followed by computational analysis of the collected measurements. Standardized workflows provide the common structure needed to compare samples or conditions consistently. This sequence supports an integrated path from experimental measurement to dataset interpretation without relying only on one assay at a time.
In immunology research, these approaches can compare immune-cell responses across experimental conditions, helping investigators examine how cellular reactions vary within a larger dataset. In infection studies, the same strategy can characterize pathogen-associated signals. Considering both response types at scale supports systematic analysis of host-pathogen interactions rather than relying on isolated measurements.
High-throughput methodology can address two applied needs highlighted in immunology and infection research: evaluating diagnostic markers and screening candidate antimicrobial or immunomodulatory treatments. Processing many samples or conditions allows these markers and candidates to be examined comparatively. The resulting dataset supports data-driven interpretation of findings relevant to diagnosis or treatment research.
Host-pathogen studies benefit from combining large-scale measurements with computational interpretation. This pairing can reveal relationships among immune-cell responses, pathogen-associated signals, diagnostic markers, and treatment-related conditions. Because patterns may be missed in individual assays, high-throughput methodology provides a broader basis for examining infection-related biology and comparing possible interventions.